1. Field of the Invention
This invention relates to an image data processing method and a device for realizing it and more in detail to an image data processing method and a device for realizing it, in which original images are restored by treating stochastically image data deteriorated by noises, etc. by means of a computer.
2. Description of the Prior Art
One of the treatment methods for restoring images deteriorated by noises, non-linear characteristics of a converter system, etc. consists in detection or clarification of edges and in order to effect it, heretofore, the Laplacian processing has been often utilized. A Laplacian in image data means a variable quantity representing the difference between gray levels of pixels adjacent to each other in the line or direction and it can be given by the following formula: ##EQU2## where x.sub.i,j represents the gray level of the pixel at the i-th row and the j-th line. Since the absolute value of the Laplacian has in general a great value at a point, where the pixel gray level begins to vary rapidly, it is efficacious for detecting the edge of an image pattern.
However the absolute value of the Laplacian is great also at a point, where the pixel gray level varies rapidly because of noises. Consequently the Laplacian processing provokes accentuation of the noises at the same time as the detection of the edge and as the result makes elimination of the noises difficult. On the other hand, if any smoothing processing is effected in order to remove the noises, not only it removes the noises, but also it makes the edge vague, what makes the detection thereof difficult. Studies on the integrating image restoration reconciling these two processings, which seem at first sight to be hardly consistent with each other, have not been noticeably developed up to the latest date.
An example of image data processings, by which noise components are removed by effecting iteratively treatments to update pixel values according to a predetermined rule, while checking the relation between the value of each of the pixels and that of pixels adjacent thereto, has been reported in an article entitled "Stochastic Relaxations, Gibbs Distributions, and Bayesian Restoration of Images" in IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, Vol. PAM I-6, No. 6, November 1984, pp. 721-741. In the image data processing described in this article a quantity called "energy function" represented by a function of the gray level of each of the pixels, the gray level of the pixels adjacent thereto and boundary elements, which can exist therebetween. A restored image is obtained by effecting a treatment to modify stochastically the gray level of each of the pixels so that the value of a probability determined by this energy function and by iterating this process, while reducing progressively a parameter called temperature.
Although the article stated above suggests that the algorithm of the image data processing described above is suitable for parallel treatments, it discloses no concrete construction of the processing device therefor.
Further the description of the article stated above is highly scientific and abstract and how the energy function stated above or a function called potential, on the basis of which the energy function is formed, can be determined concretely is not disclosed there. For this reason it is a problem how the energy function permitting to make the elimination of noises and the detection of pattern edges compatible, when putting it to practical use, is determined concretely.